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We propose an iterative raster scan algorithm for superpixel segmentation, which is based on the K-means clustering algorithm. The proposed algorithm updates the class label of each pixel only at the ...boundaries of superpixels in a raster scan order, and refers to only two neighboring pixels per pixel for updating the variables. Therefore, the proposed algorithm is computationally efficient compared with existing methods. Experimental results show that the proposed algorithm generates compact and adherent superpixels in a finite number of iterations of the raster scan process.続きを見る
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